TY  - GEN
AU  - Hamori,Shigeyuki
TI  - Empirical Finance
SN  - books978-3-03897-707-0
PY  - 2019///
PB  - MDPI - Multidisciplinary Digital Publishing Institute
KW  - n/a
KW  - short-term forecasting
KW  - wavelet transform
KW  - IPO
KW  - volatility
KW  - US dollar
KW  - institutional investors' shareholdings
KW  - neural network
KW  - financial market stress
KW  - market microstructure
KW  - text similarity
KW  - TVP-VAR model
KW  - Japanese yen
KW  - convolutional neural networks
KW  - global financial crisis
KW  - deep neural network
KW  - cross-correlation function
KW  - boosting
KW  - causality-in-variance
KW  - flight to quality
KW  - bagging
KW  - earnings quality
KW  - algorithmic trading
KW  - stop loss
KW  - statistical arbitrage
KW  - ensemble learning
KW  - liquidity risk premium
KW  - gold return
KW  - futures market
KW  - take profit
KW  - currency crisis
KW  - spark spread
KW  - city banks
KW  - piecewise regression model
KW  - financial and non-financial variables
KW  - exports
KW  - data mining
KW  - latency
KW  - crude oil futures prices forecasting
KW  - random forests
KW  - wholesale electricity
KW  - SVM
KW  - random forest
KW  - bank credit
KW  - deep learning
KW  - Vietnam
KW  - inertia
KW  - MACD
KW  - initial public offering
KW  - text mining
KW  - bankruptcy prediction
KW  - exchange rate
KW  - asset pricing model
KW  - LSTM
KW  - panel data model
KW  - structural break
KW  - credit risk
KW  - housing and stock markets
KW  - copula
KW  - ARDL
KW  - earnings manipulation
KW  - machine learning
KW  - natural gas
KW  - housing price
KW  - asymmetric dependence
KW  - real estate development loans
KW  - earnings management
KW  - cointegration
KW  - predictive accuracy
KW  - robust regression
KW  - quantile regression
KW  - dependence structure
KW  - housing loans
KW  - price discovery
KW  - utility of international currency
KW  - ATR
N1  - Open Access
N2  - There is no denying the role of empirical research in finance and the remarkable progress of empirical techniques in this research field. This Special Issue focuses on the broad topic of "Empirical Finance" and includes novel empirical research associated with financial data. One example includes the application of novel empirical techniques, such as machine learning, data mining, wavelet transform, copula analysis, and TV-VAR, to financial data. The Special Issue includes contributions on empirical finance, such as algorithmic trading, market efficiency, market microstructure, portfolio theory and asset allocation, asset pricing models, liquidity risk premium, currency crisis, return predictability, and volatility modeling
UR  - https://mdpi.com/books/pdfview/book/1181
UR  - https://directory.doabooks.org/handle/20.500.12854/46295
ER  -